After obtaining the keypoint descriptors, SIFT matches a set of keypoints from one image to a set of keypoints in another image by comparing the L2 norm of their residuals.
In the original publication, SIFT used the Best Bin First [1]} algorithm to find approximate nearest neighbors and speed up the matching process.
This process does not always return the nearest neighbor.
Since we are interested in the ability of the methods to produce feature descriptors, we decided to use the global minimum of the L2 norm of the residuals instead.
